Prepared Report - Visualization edísön

Dataset statistics

Number of variables	19
Number of observations	248,245
Missing cells	0
Missing cells (%)	0.0%
Duplicate rows	153
Duplicate rows (%)	0.1%
Total size in memory	36.0 MiB
Average record size in memory	152.0 B

Variable types

Categorical	10
Numeric	8
DateTime	1

Alerts

Dataset has 153 (0.1%) duplicate rows	Duplicates
`active_days` is highly overall correlated with `ad_view_cnt`	High correlation
`ad_view_cnt` is highly overall correlated with `active_days`	High correlation
`city` is highly overall correlated with `postcode`	High correlation
`postcode` is highly overall correlated with `city`	High correlation
`property_subtype` is highly imbalanced (59.3%)	Imbalance
`garden_access` is highly imbalanced (78.5%)	Imbalance
`building_floor_count` has 2987 (1.2%) zeros	Zeros
`balcony_area` has 162843 (65.6%) zeros	Zeros

Reproduction

Analysis started	2025-03-30 20:03:41.151771
Analysis finished	2025-03-30 20:03:49.713193
Duration	8.56 seconds
Software version	ydata-profiling vv4.14.0
Download configuration	config.json

city
Categorical

High correlation

Distinct	23
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.9 MiB

Budapest XIV.	27583
Budapest XIII.	27191
Budapest XI.	21974
Budapest VII.	19568
Budapest III.	18069
Other values (18)	133860

Length

Max length	15
Median length	14
Mean length	12.734198
Min length	11

Characters and Unicode

Total characters	3,161,201
Distinct characters	13
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	Budapest I.
2nd row	Budapest I.
3rd row	Budapest I.
4th row	Budapest I.
5th row	Budapest I.

Common Values

Value	Count	Frequency (%)
Budapest XIV.	27583	11.1%
Budapest XIII.	27191	11.0%
Budapest XI.	21974	8.9%
Budapest VII.	19568	7.9%
Budapest III.	18069	7.3%
Budapest VIII.	17668	7.1%
Budapest VI.	14293	5.8%
Budapest IX.	12166	4.9%
Budapest IV.	10725	4.3%
Budapest II.	10329	4.2%
Other values (13)	68679	27.7%

Length

Histogram of lengths of the category

Value	Count	Frequency (%)
budapest	248245	50.0%
xiv	27583	5.6%
xiii	27191	5.5%
xi	21974	4.4%
vii	19568	3.9%
iii	18069	3.6%
viii	17668	3.6%
vi	14293	2.9%
ix	12166	2.5%
iv	10725	2.2%
Other values (14)	79008	15.9%

Most occurring characters

Value	Count	Frequency (%)
I	396246	12.5%
u	248245	7.9%
d	248245	7.9%
a	248245	7.9%
B	248245	7.9%
p	248245	7.9%
e	248245	7.9%
t	248245	7.9%
s	248245	7.9%
	248245	7.9%
Other values (3)	530750	16.8%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	3161201	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
I	396246	12.5%
u	248245	7.9%
d	248245	7.9%
a	248245	7.9%
B	248245	7.9%
p	248245	7.9%
e	248245	7.9%
t	248245	7.9%
s	248245	7.9%
	248245	7.9%
Other values (3)	530750	16.8%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	3161201	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
I	396246	12.5%
u	248245	7.9%
d	248245	7.9%
a	248245	7.9%
B	248245	7.9%
p	248245	7.9%
e	248245	7.9%
t	248245	7.9%
s	248245	7.9%
	248245	7.9%
Other values (3)	530750	16.8%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	3161201	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
I	396246	12.5%
u	248245	7.9%
d	248245	7.9%
a	248245	7.9%
B	248245	7.9%
p	248245	7.9%
e	248245	7.9%
t	248245	7.9%
s	248245	7.9%
	248245	7.9%
Other values (3)	530750	16.8%

postcode
Real number (ℝ)

High correlation

Distinct	162
Distinct (%)	0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	1104.5512

Minimum	1011
Maximum	1239
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.9 MiB

Quantile statistics

Minimum	1011
5-th percentile	1026
Q1	1066
median	1108
Q3	1141
95-th percentile	1201
Maximum	1239
Range	228
Interquartile range (IQR)	75

Descriptive statistics

Standard deviation	51.232663
Coefficient of variation (CV)	0.046383239
Kurtosis	-0.66538183
Mean	1104.5512
Median Absolute Deviation (MAD)	36
Skewness	0.19755779
Sum	2.7419932 × 10⁸
Variance	2624.7858
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1141	13789	5.6%
1131	12205	4.9%
1111	10919	4.4%
1081	8738	3.5%
1071	8648	3.5%
1031	6441	2.6%
1041	6136	2.5%
1021	5210	2.1%
1101	4700	1.9%
1039	4529	1.8%
Other values (152)	166930	67.2%

Value	Count	Frequency (%)
1011	1654	0.7%
1012	605	0.2%
1013	275	0.1%
1014	217	0.1%
1015	669	0.3%
1016	1087	0.4%
1021	5210	2.1%
1022	507	0.2%
1023	266	0.1%
1024	1160	0.5%

Value	Count	Frequency (%)
1239	15	< 0.1%
1238	88	< 0.1%
1237	199	0.1%
1231	27	< 0.1%
1225	154	0.1%
1224	159	0.1%
1223	87	< 0.1%
1222	191	0.1%
1221	1285	0.5%
1215	63	< 0.1%

property_subtype
Categorical

Imbalance

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.9 MiB

brick flat (for sale)	185735
prefabricated panel flat (for sale)	62506
terraced house	3
prefabricated panel flat (for rent)	1

Length

Max length	35
Median length	21
Mean length	24.525054
Min length	14

Characters and Unicode

Total characters	6,088,222
Distinct characters	20
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	1 ?
Unique (%)	< 0.1%

Sample

1st row	brick flat (for sale)
2nd row	brick flat (for sale)
3rd row	brick flat (for sale)
4th row	brick flat (for sale)
5th row	brick flat (for sale)

Common Values

Value	Count	Frequency (%)
brick flat (for sale)	185735	74.8%
prefabricated panel flat (for sale)	62506	25.2%
terraced house	3	< 0.1%
prefabricated panel flat (for rent)	1	< 0.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
flat	248242	23.5%
for	248242	23.5%
sale	248241	23.5%
brick	185735	17.6%
prefabricated	62507	5.9%
panel	62507	5.9%
terraced	3	< 0.1%
house	3	< 0.1%
rent	1	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
	807236	13.3%
a	684007	11.2%
r	558998	9.2%
f	558991	9.2%
l	558990	9.2%
e	435772	7.2%
t	310753	5.1%
c	248245	4.1%
o	248245	4.1%
s	248244	4.1%
Other values (10)	1428741	23.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	6088222	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
	807236	13.3%
a	684007	11.2%
r	558998	9.2%
f	558991	9.2%
l	558990	9.2%
e	435772	7.2%
t	310753	5.1%
c	248245	4.1%
o	248245	4.1%
s	248244	4.1%
Other values (10)	1428741	23.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	6088222	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
	807236	13.3%
a	684007	11.2%
r	558998	9.2%
f	558991	9.2%
l	558990	9.2%
e	435772	7.2%
t	310753	5.1%
c	248245	4.1%
o	248245	4.1%
s	248244	4.1%
Other values (10)	1428741	23.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	6088222	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
	807236	13.3%
a	684007	11.2%
r	558998	9.2%
f	558991	9.2%
l	558990	9.2%
e	435772	7.2%
t	310753	5.1%
c	248245	4.1%
o	248245	4.1%
s	248244	4.1%
Other values (10)	1428741	23.5%

property_condition_type
Categorical

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.9 MiB

3	122574
4	60992
2	35626
1	29053

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	248,245
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	2
2nd row	3
3rd row	4
4th row	2
5th row	3

Common Values

Value	Count	Frequency (%)
3	122574	49.4%
4	60992	24.6%
2	35626	14.4%
1	29053	11.7%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
3	122574	49.4%
4	60992	24.6%
2	35626	14.4%
1	29053	11.7%

Most occurring characters

Value	Count	Frequency (%)
3	122574	49.4%
4	60992	24.6%
2	35626	14.4%
1	29053	11.7%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	248245	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
3	122574	49.4%
4	60992	24.6%
2	35626	14.4%
1	29053	11.7%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	248245	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
3	122574	49.4%
4	60992	24.6%
2	35626	14.4%
1	29053	11.7%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	248245	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
3	122574	49.4%
4	60992	24.6%
2	35626	14.4%
1	29053	11.7%

property_floor
Real number (ℝ)

Distinct	7
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.9539487

Minimum	0
Maximum	6
Zeros	1430
Zeros (%)	0.6%
Negative	0
Negative (%)	0.0%
Memory size	1.9 MiB

Quantile statistics

Minimum	0
5-th percentile	1
Q1	3
median	3
Q3	4
95-th percentile	5
Maximum	6
Range	6
Interquartile range (IQR)	1

Descriptive statistics

Standard deviation	1.1120234
Coefficient of variation (CV)	0.37645318
Kurtosis	0.092219119
Mean	2.9539487
Median Absolute Deviation (MAD)	0
Skewness	-0.29711332
Sum	733303
Variance	1.236596
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=7)

Value	Count	Frequency (%)
3	132036	53.2%
4	45737	18.4%
1	39260	15.8%
5	16257	6.5%
2	11862	4.8%
6	1663	0.7%
0	1430	0.6%

Value	Count	Frequency (%)
0	1430	0.6%
1	39260	15.8%
2	11862	4.8%
3	132036	53.2%
4	45737	18.4%
5	16257	6.5%
6	1663	0.7%

Value	Count	Frequency (%)
6	1663	0.7%
5	16257	6.5%
4	45737	18.4%
3	132036	53.2%
2	11862	4.8%
1	39260	15.8%
0	1430	0.6%

building_floor_count
Real number (ℝ)

Zeros

Distinct	6
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	0.34117505

Minimum	-1
Maximum	4
Zeros	2987
Zeros (%)	1.2%
Negative	136138
Negative (%)	54.8%
Memory size	1.9 MiB

Quantile statistics

Minimum	-1
5-th percentile	-1
Q1	-1
median	-1
Q3	2
95-th percentile	3
Maximum	4
Range	5
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	1.5939341
Coefficient of variation (CV)	4.6718954
Kurtosis	-1.2462284
Mean	0.34117505
Median Absolute Deviation (MAD)	0
Skewness	0.58757459
Sum	84695
Variance	2.5406261
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=6)

Value	Count	Frequency (%)
-1	136138	54.8%
2	40484	16.3%
1	34349	13.8%
3	31632	12.7%
0	2987	1.2%
4	2655	1.1%

Value	Count	Frequency (%)
-1	136138	54.8%
0	2987	1.2%
1	34349	13.8%
2	40484	16.3%
3	31632	12.7%
4	2655	1.1%

Value	Count	Frequency (%)
4	2655	1.1%
3	31632	12.7%
2	40484	16.3%
1	34349	13.8%
0	2987	1.2%
-1	136138	54.8%

view_type
Categorical

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.9 MiB

0.0	114263
1.0	53924
3.0	35065
2.0	29204
4.0	15789

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	744,735
Distinct characters	6
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	2.0
3rd row	0.0
4th row	0.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
0.0	114263	46.0%
1.0	53924	21.7%
3.0	35065	14.1%
2.0	29204	11.8%
4.0	15789	6.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0.0	114263	46.0%
1.0	53924	21.7%
3.0	35065	14.1%
2.0	29204	11.8%
4.0	15789	6.4%

Most occurring characters

Value	Count	Frequency (%)
0	362508	48.7%
.	248245	33.3%
1	53924	7.2%
3	35065	4.7%
2	29204	3.9%
4	15789	2.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	744735	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	362508	48.7%
.	248245	33.3%
1	53924	7.2%
3	35065	4.7%
2	29204	3.9%
4	15789	2.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	744735	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	362508	48.7%
.	248245	33.3%
1	53924	7.2%
3	35065	4.7%
2	29204	3.9%
4	15789	2.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	744735	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	362508	48.7%
.	248245	33.3%
1	53924	7.2%
3	35065	4.7%
2	29204	3.9%
4	15789	2.1%

orientation
Categorical

Distinct	4
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.9 MiB

0	95637
3	72494
2	59097
1	21017

Length

Max length	1
Median length	1
Mean length	1
Min length	1

Characters and Unicode

Total characters	248,245
Distinct characters	4
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1
2nd row	2
3rd row	2
4th row	0
5th row	0

Common Values

Value	Count	Frequency (%)
0	95637	38.5%
3	72494	29.2%
2	59097	23.8%
1	21017	8.5%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0	95637	38.5%
3	72494	29.2%
2	59097	23.8%
1	21017	8.5%

Most occurring characters

Value	Count	Frequency (%)
0	95637	38.5%
3	72494	29.2%
2	59097	23.8%
1	21017	8.5%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	248245	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	95637	38.5%
3	72494	29.2%
2	59097	23.8%
1	21017	8.5%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	248245	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	95637	38.5%
3	72494	29.2%
2	59097	23.8%
1	21017	8.5%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	248245	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	95637	38.5%
3	72494	29.2%
2	59097	23.8%
1	21017	8.5%

garden_access
Categorical

Imbalance

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.9 MiB

none	239759
yes	8486

Length

Max length	4
Median length	4
Mean length	3.965816
Min length	3

Characters and Unicode

Total characters	984,494
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	none
2nd row	none
3rd row	none
4th row	none
5th row	none

Common Values

Value	Count	Frequency (%)
none	239759	96.6%
yes	8486	3.4%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
none	239759	96.6%
yes	8486	3.4%

Most occurring characters

Value	Count	Frequency (%)
n	479518	48.7%
e	248245	25.2%
o	239759	24.4%
y	8486	0.9%
s	8486	0.9%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	984494	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
n	479518	48.7%
e	248245	25.2%
o	239759	24.4%
y	8486	0.9%
s	8486	0.9%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	984494	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
n	479518	48.7%
e	248245	25.2%
o	239759	24.4%
y	8486	0.9%
s	8486	0.9%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	984494	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
n	479518	48.7%
e	248245	25.2%
o	239759	24.4%
y	8486	0.9%
s	8486	0.9%

heating_type
Categorical

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.9 MiB

2.0	132125
1.0	71397
0.0	34830
3.0	6957
4.0	2936

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	744,735
Distinct characters	6
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	3.0
2nd row	2.0
3rd row	1.0
4th row	2.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
2.0	132125	53.2%
1.0	71397	28.8%
0.0	34830	14.0%
3.0	6957	2.8%
4.0	2936	1.2%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
2.0	132125	53.2%
1.0	71397	28.8%
0.0	34830	14.0%
3.0	6957	2.8%
4.0	2936	1.2%

Most occurring characters

Value	Count	Frequency (%)
0	283075	38.0%
.	248245	33.3%
2	132125	17.7%
1	71397	9.6%
3	6957	0.9%
4	2936	0.4%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	744735	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	283075	38.0%
.	248245	33.3%
2	132125	17.7%
1	71397	9.6%
3	6957	0.9%
4	2936	0.4%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	744735	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	283075	38.0%
.	248245	33.3%
2	132125	17.7%
1	71397	9.6%
3	6957	0.9%
4	2936	0.4%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	744735	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	283075	38.0%
.	248245	33.3%
2	132125	17.7%
1	71397	9.6%
3	6957	0.9%
4	2936	0.4%

elevator_type
Categorical

Distinct	2
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.9 MiB

none	137113
yes	111132

Length

Max length	4
Median length	4
Mean length	3.5523294
Min length	3

Characters and Unicode

Total characters	881,848
Distinct characters	5
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	yes
2nd row	yes
3rd row	none
4th row	none
5th row	yes

Common Values

Value	Count	Frequency (%)
none	137113	55.2%
yes	111132	44.8%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
none	137113	55.2%
yes	111132	44.8%

Most occurring characters

Value	Count	Frequency (%)
n	274226	31.1%
e	248245	28.2%
o	137113	15.5%
y	111132	12.6%
s	111132	12.6%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	881848	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
n	274226	31.1%
e	248245	28.2%
o	137113	15.5%
y	111132	12.6%
s	111132	12.6%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	881848	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
n	274226	31.1%
e	248245	28.2%
o	137113	15.5%
y	111132	12.6%
s	111132	12.6%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	881848	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
n	274226	31.1%
e	248245	28.2%
o	137113	15.5%
y	111132	12.6%
s	111132	12.6%

room_cnt
Categorical

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.9 MiB

1.0	141726
2.0	93526
3.0	11857
0.0	916
4.0	220

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	744,735
Distinct characters	6
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	1.0
2nd row	1.0
3rd row	1.0
4th row	1.0
5th row	1.0

Common Values

Value	Count	Frequency (%)
1.0	141726	57.1%
2.0	93526	37.7%
3.0	11857	4.8%
0.0	916	0.4%
4.0	220	0.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
1.0	141726	57.1%
2.0	93526	37.7%
3.0	11857	4.8%
0.0	916	0.4%
4.0	220	0.1%

Most occurring characters

Value	Count	Frequency (%)
0	249161	33.5%
.	248245	33.3%
1	141726	19.0%
2	93526	12.6%
3	11857	1.6%
4	220	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	744735	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	249161	33.5%
.	248245	33.3%
1	141726	19.0%
2	93526	12.6%
3	11857	1.6%
4	220	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	744735	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	249161	33.5%
.	248245	33.3%
1	141726	19.0%
2	93526	12.6%
3	11857	1.6%
4	220	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	744735	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	249161	33.5%
.	248245	33.3%
1	141726	19.0%
2	93526	12.6%
3	11857	1.6%
4	220	< 0.1%

small_room_cnt
Categorical

Distinct	5
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Memory size	1.9 MiB

0.0	143082
1.0	75962
2.0	27893
3.0	1260
4.0	48

Length

Max length	3
Median length	3
Mean length	3
Min length	3

Characters and Unicode

Total characters	744,735
Distinct characters	6
Distinct categories	1 ?
Distinct scripts	1 ?
Distinct blocks	1 ?

The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique	0 ?
Unique (%)	0.0%

Sample

1st row	0.0
2nd row	1.0
3rd row	1.0
4th row	0.0
5th row	2.0

Common Values

Value	Count	Frequency (%)
0.0	143082	57.6%
1.0	75962	30.6%
2.0	27893	11.2%
3.0	1260	0.5%
4.0	48	< 0.1%

Length

Histogram of lengths of the category

Common Values (Plot)

Value	Count	Frequency (%)
0.0	143082	57.6%
1.0	75962	30.6%
2.0	27893	11.2%
3.0	1260	0.5%
4.0	48	< 0.1%

Most occurring characters

Value	Count	Frequency (%)
0	391327	52.5%
.	248245	33.3%
1	75962	10.2%
2	27893	3.7%
3	1260	0.2%
4	48	< 0.1%

Most occurring categories

Value	Count	Frequency (%)
(unknown)	744735	100.0%

Most frequent character per category

(unknown)

Value	Count	Frequency (%)
0	391327	52.5%
.	248245	33.3%
1	75962	10.2%
2	27893	3.7%
3	1260	0.2%
4	48	< 0.1%

Most occurring scripts

Value	Count	Frequency (%)
(unknown)	744735	100.0%

Most frequent character per script

(unknown)

Value	Count	Frequency (%)
0	391327	52.5%
.	248245	33.3%
1	75962	10.2%
2	27893	3.7%
3	1260	0.2%
4	48	< 0.1%

Most occurring blocks

Value	Count	Frequency (%)
(unknown)	744735	100.0%

Most frequent character per block

(unknown)

Value	Count	Frequency (%)
0	391327	52.5%
.	248245	33.3%
1	75962	10.2%
2	27893	3.7%
3	1260	0.2%
4	48	< 0.1%

created_at
Date

Distinct	568
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Memory size	1.9 MiB

Minimum	2015-02-09 00:00:00
Maximum	2016-08-29 00:00:00
Invalid dates	0
Invalid dates (%)	0.0%

Histogram with fixed size bins (bins=50)

property_area
Real number (ℝ)

Distinct	14
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	48.601382

Minimum	5
Maximum	70
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.9 MiB

Quantile statistics

Minimum	5
5-th percentile	25
Q1	40
median	50
Q3	60
95-th percentile	70
Maximum	70
Range	65
Interquartile range (IQR)	20

Descriptive statistics

Standard deviation	12.67771
Coefficient of variation (CV)	0.26085081
Kurtosis	-0.76144877
Mean	48.601382
Median Absolute Deviation (MAD)	10
Skewness	-0.21353866
Sum	12065050
Variance	160.72433
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=14)

Value	Count	Frequency (%)
50	38510	15.5%
55	38170	15.4%
45	27605	11.1%
35	27021	10.9%
60	25618	10.3%
65	23529	9.5%
40	20961	8.4%
30	18190	7.3%
70	15635	6.3%
25	10382	4.2%
Other values (4)	2624	1.1%

Value	Count	Frequency (%)
5	31	< 0.1%
10	170	0.1%
15	536	0.2%
20	1887	0.8%
25	10382	4.2%
30	18190	7.3%
35	27021	10.9%
40	20961	8.4%
45	27605	11.1%
50	38510	15.5%

Value	Count	Frequency (%)
70	15635	6.3%
65	23529	9.5%
60	25618	10.3%
55	38170	15.4%
50	38510	15.5%
45	27605	11.1%
40	20961	8.4%
35	27021	10.9%
30	18190	7.3%
25	10382	4.2%

balcony_area
Real number (ℝ)

Zeros

Distinct	90
Distinct (%)	< 0.1%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	2.0347358

Minimum	0
Maximum	96
Zeros	162843
Zeros (%)	65.6%
Negative	0
Negative (%)	0.0%
Memory size	1.9 MiB

Quantile statistics

Minimum	0
5-th percentile	0
Q1	0
median	0
Q3	3
95-th percentile	8
Maximum	96
Range	96
Interquartile range (IQR)	3

Descriptive statistics

Standard deviation	4.7490332
Coefficient of variation (CV)	2.3339802
Kurtosis	86.857593
Mean	2.0347358
Median Absolute Deviation (MAD)	0
Skewness	7.1329109
Sum	505113
Variance	22.553316
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
0	162843	65.6%
4	22867	9.2%
3	15612	6.3%
5	9335	3.8%
2	8145	3.3%
6	7861	3.2%
8	3750	1.5%
7	3745	1.5%
1	2438	1.0%
10	2182	0.9%
Other values (80)	9467	3.8%

Value	Count	Frequency (%)
0	162843	65.6%
1	2438	1.0%
2	8145	3.3%
3	15612	6.3%
4	22867	9.2%
5	9335	3.8%
6	7861	3.2%
7	3745	1.5%
8	3750	1.5%
9	1624	0.7%

Value	Count	Frequency (%)
96	16	< 0.1%
90	43	< 0.1%
88	5	< 0.1%
87	5	< 0.1%
86	1	< 0.1%
85	4	< 0.1%
84	5	< 0.1%
83	10	< 0.1%
82	15	< 0.1%
81	1	< 0.1%

price_created_at
Real number (ℝ)

Distinct	574
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	19.380841

Minimum	0.1
Maximum	60
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.9 MiB

Quantile statistics

Minimum	0.1
5-th percentile	9.1
Q1	13.3
median	16.9
Q3	23.9
95-th percentile	36.5
Maximum	60
Range	59.9
Interquartile range (IQR)	10.6

Descriptive statistics

Standard deviation	8.6301052
Coefficient of variation (CV)	0.44529054
Kurtosis	1.9311099
Mean	19.380841
Median Absolute Deviation (MAD)	4.6
Skewness	1.2755812
Sum	4811196.9
Variance	74.478716
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
14.9	5600	2.3%
12.9	5327	2.1%
13.9	5276	2.1%
15.9	4698	1.9%
13.5	4560	1.8%
19.9	4502	1.8%
16.9	3941	1.6%
12.5	3940	1.6%
18.9	3749	1.5%
11.9	3585	1.4%
Other values (564)	203067	81.8%

Value	Count	Frequency (%)
0.1	1	< 0.1%
0.2	2	< 0.1%
0.5	2	< 0.1%
0.6	1	< 0.1%
0.7	1	< 0.1%
0.8	2	< 0.1%
0.9	1	< 0.1%
1	7	< 0.1%
1.3	1	< 0.1%
1.5	2	< 0.1%

Value	Count	Frequency (%)
60	31	< 0.1%
59.9	106	< 0.1%
59.8	40	< 0.1%
59.7	2	< 0.1%
59.6	3	< 0.1%
59.5	8	< 0.1%
59.4	2	< 0.1%
59.3	1	< 0.1%
59.2	11	< 0.1%
59.1	5	< 0.1%

ad_view_cnt
Real number (ℝ)

High correlation

Distinct	3835
Distinct (%)	1.5%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	243.44106

Minimum	0
Maximum	40248
Zeros	22
Zeros (%)	< 0.1%
Negative	0
Negative (%)	0.0%
Memory size	1.9 MiB

Quantile statistics

Minimum	0
5-th percentile	13
Q1	40
median	97
Q3	246
95-th percentile	930
Maximum	40248
Range	40248
Interquartile range (IQR)	206

Descriptive statistics

Standard deviation	508.28378
Coefficient of variation (CV)	2.0879131
Kurtosis	499.34869
Mean	243.44106
Median Absolute Deviation (MAD)	70
Skewness	12.993082
Sum	60433027
Variance	258352.4
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
24	1978	0.8%
17	1970	0.8%
25	1963	0.8%
28	1946	0.8%
18	1945	0.8%
22	1938	0.8%
26	1934	0.8%
23	1931	0.8%
20	1926	0.8%
19	1908	0.8%
Other values (3825)	228806	92.2%

Value	Count	Frequency (%)
0	22	< 0.1%
1	82	< 0.1%
2	204	0.1%
3	335	0.1%
4	493	0.2%
5	655	0.3%
6	906	0.4%
7	1079	0.4%
8	1196	0.5%
9	1347	0.5%

Value	Count	Frequency (%)
40248	1	< 0.1%
36988	1	< 0.1%
30012	1	< 0.1%
28096	1	< 0.1%
22574	1	< 0.1%
21410	1	< 0.1%
20277	1	< 0.1%
19592	1	< 0.1%
18914	1	< 0.1%
17668	1	< 0.1%

active_days
Real number (ℝ)

High correlation

Distinct	441
Distinct (%)	0.2%
Missing	0
Missing (%)	0.0%
Infinite	0
Infinite (%)	0.0%
Mean	44.219912

Minimum	1
Maximum	544
Zeros	0
Zeros (%)	0.0%
Negative	0
Negative (%)	0.0%
Memory size	1.9 MiB

Quantile statistics

Minimum	1
5-th percentile	2
Q1	11
median	28
Q3	61
95-th percentile	141
Maximum	544
Range	543
Interquartile range (IQR)	50

Descriptive statistics

Standard deviation	47.944076
Coefficient of variation (CV)	1.0842192
Kurtosis	7.2197882
Mean	44.219912
Median Absolute Deviation (MAD)	20
Skewness	2.2345011
Sum	10977372
Variance	2298.6344
Monotonicity	Not monotonic

Histogram with fixed size bins (bins=50)

Value	Count	Frequency (%)
1	7049	2.8%
6	6509	2.6%
7	6291	2.5%
2	6243	2.5%
3	6080	2.4%
5	5962	2.4%
4	5717	2.3%
8	5421	2.2%
14	5188	2.1%
13	4779	1.9%
Other values (431)	189006	76.1%

Value	Count	Frequency (%)
1	7049	2.8%
2	6243	2.5%
3	6080	2.4%
4	5717	2.3%
5	5962	2.4%
6	6509	2.6%
7	6291	2.5%
8	5421	2.2%
9	4649	1.9%
10	4517	1.8%

Value	Count	Frequency (%)
544	1	< 0.1%
540	1	< 0.1%
537	1	< 0.1%
535	1	< 0.1%
528	3	< 0.1%
520	1	< 0.1%
511	1	< 0.1%
510	1	< 0.1%
487	1	< 0.1%
485	2	< 0.1%

	active_days	ad_view_cnt	balcony_area	building_floor_count	city	elevator_type	garden_access	heating_type	orientation	postcode	price_created_at	property_area	property_condition_type	property_floor	property_subtype	room_cnt	small_room_cnt	view_type
active_days	1.000	0.532	0.003	0.057	0.021	0.046	0.062	0.012	0.011	-0.008	0.089	0.067	0.006	-0.045	0.042	0.027	0.011	0.034
ad_view_cnt	0.532	1.000	0.089	0.369	0.008	0.008	0.018	0.009	0.003	0.014	-0.149	-0.011	0.012	-0.033	0.003	0.000	0.000	0.015
balcony_area	0.003	0.089	1.000	0.154	0.049	0.041	0.158	0.066	0.034	0.138	0.194	0.245	0.116	0.180	0.062	0.031	0.027	0.058
building_floor_count	0.057	0.369	0.154	1.000	0.174	0.481	0.353	0.178	0.082	0.023	-0.069	0.044	0.120	0.157	0.291	0.062	0.075	0.341
city	0.021	0.008	0.049	0.174	1.000	0.261	0.114	0.195	0.103	0.952	0.222	0.115	0.099	0.140	0.307	0.091	0.158	0.191
elevator_type	0.046	0.008	0.041	0.481	0.261	1.000	0.079	0.364	0.175	0.154	0.146	0.182	0.117	0.434	0.358	0.096	0.129	0.190
garden_access	0.062	0.018	0.158	0.353	0.114	0.079	1.000	0.036	0.050	0.084	0.062	0.037	0.040	0.248	0.098	0.005	0.019	0.198
heating_type	0.012	0.009	0.066	0.178	0.195	0.364	0.036	1.000	0.057	0.160	0.149	0.181	0.177	0.191	0.269	0.084	0.125	0.130
orientation	0.011	0.003	0.034	0.082	0.103	0.175	0.050	0.057	1.000	0.077	0.047	0.041	0.064	0.063	0.079	0.016	0.031	0.083
postcode	-0.008	0.014	0.138	0.023	0.952	0.154	0.084	0.160	0.077	1.000	-0.281	0.008	0.078	0.062	0.216	0.063	0.131	0.163
price_created_at	0.089	-0.149	0.194	-0.069	0.222	0.146	0.062	0.149	0.047	-0.281	1.000	0.482	0.187	0.016	0.199	0.164	0.069	0.051
property_area	0.067	-0.011	0.245	0.044	0.115	0.182	0.037	0.181	0.041	0.008	0.482	1.000	0.040	0.156	0.141	0.345	0.213	0.106
property_condition_type	0.006	0.012	0.116	0.120	0.099	0.117	0.040	0.177	0.064	0.078	0.187	0.040	1.000	0.054	0.098	0.021	0.046	0.114
property_floor	-0.045	-0.033	0.180	0.157	0.140	0.434	0.248	0.191	0.063	0.062	0.016	0.156	0.054	1.000	0.285	0.055	0.082	0.174
property_subtype	0.042	0.003	0.062	0.291	0.307	0.358	0.098	0.269	0.079	0.216	0.199	0.141	0.098	0.285	1.000	0.076	0.165	0.141
room_cnt	0.027	0.000	0.031	0.062	0.091	0.096	0.005	0.084	0.016	0.063	0.164	0.345	0.021	0.055	0.076	1.000	0.198	0.049
small_room_cnt	0.011	0.000	0.027	0.075	0.158	0.129	0.019	0.125	0.031	0.131	0.069	0.213	0.046	0.082	0.165	0.198	1.000	0.058
view_type	0.034	0.015	0.058	0.341	0.191	0.190	0.198	0.130	0.083	0.163	0.051	0.106	0.114	0.174	0.141	0.049	0.058	1.000

A simple visualization of nullity by column.

Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

	city	postcode	property_subtype	property_condition_type	property_floor	building_floor_count	view_type	orientation	garden_access	heating_type	elevator_type	room_cnt	small_room_cnt	created_at	property_area	balcony_area	price_created_at	ad_view_cnt	active_days
0	Budapest I.	1015.0	brick flat (for sale)	2	4	-1.0	0.0	1	none	3.0	yes	1.0	0.0	2016-01-29	40.0	4.0	22.9	128.0	16.0
1	Budapest I.	1012.0	brick flat (for sale)	3	3	2.0	2.0	2	none	2.0	yes	1.0	1.0	2016-04-19	70.0	0.0	33.0	63.0	34.0
2	Budapest I.	1016.0	brick flat (for sale)	4	3	-1.0	0.0	2	none	1.0	none	1.0	1.0	2015-12-08	40.0	1.0	21.5	85.0	72.0
3	Budapest I.	1016.0	brick flat (for sale)	2	0	-1.0	0.0	0	none	2.0	none	1.0	0.0	2015-06-18	35.0	0.0	13.0	53.0	13.0
4	Budapest I.	1015.0	brick flat (for sale)	3	1	1.0	1.0	0	none	2.0	yes	1.0	2.0	2015-12-08	55.0	0.0	33.5	153.0	52.0
5	Budapest I.	1013.0	brick flat (for sale)	3	1	1.0	2.0	1	none	2.0	none	1.0	1.0	2015-11-04	45.0	0.0	22.5	753.0	90.0
6	Budapest I.	1012.0	brick flat (for sale)	2	3	-1.0	1.0	0	none	1.0	yes	2.0	1.0	2015-03-27	65.0	0.0	20.0	21.0	3.0
7	Budapest I.	1012.0	brick flat (for sale)	2	3	-1.0	0.0	3	none	1.0	yes	3.0	0.0	2015-03-27	65.0	0.0	20.0	41.0	4.0
8	Budapest I.	1012.0	brick flat (for sale)	3	3	1.0	1.0	3	none	2.0	yes	2.0	0.0	2015-06-03	50.0	0.0	25.0	142.0	11.0
9	Budapest I.	1016.0	brick flat (for sale)	1	6	-1.0	0.0	0	none	0.0	none	1.0	0.0	2015-06-10	40.0	0.0	13.9	732.0	34.0

	city	postcode	property_subtype	property_condition_type	property_floor	building_floor_count	view_type	orientation	garden_access	heating_type	elevator_type	room_cnt	small_room_cnt	created_at	property_area	balcony_area	price_created_at	ad_view_cnt	active_days
248235	Budapest XIV.	1141.0	brick flat (for sale)	4	3	-1.0	0.0	2	none	2.0	none	1.0	1.0	2016-08-24	35.0	0.0	16.0	126.0	2.0
248236	Budapest XI.	1111.0	brick flat (for sale)	3	4	-1.0	0.0	3	none	2.0	yes	1.0	1.0	2016-08-25	40.0	0.0	21.9	36.0	4.0
248237	Budapest IV.	1041.0	prefabricated panel flat (for sale)	3	5	3.0	4.0	3	none	0.0	yes	1.0	0.0	2016-08-25	35.0	0.0	13.0	81.0	1.0
248238	Budapest XI.	1111.0	brick flat (for sale)	3	4	-1.0	0.0	0	none	2.0	yes	1.0	1.0	2016-08-25	40.0	0.0	21.9	20.0	1.0
248239	Budapest XV.	1151.0	prefabricated panel flat (for sale)	4	4	-1.0	0.0	2	none	2.0	yes	1.0	1.0	2016-08-26	35.0	0.0	12.5	10.0	4.0
248240	Budapest XIII.	1131.0	brick flat (for sale)	3	1	0.0	3.0	2	yes	1.0	none	2.0	0.0	2016-08-26	50.0	0.0	15.0	268.0	3.0
248241	Budapest XII.	1121.0	brick flat (for sale)	1	2	-1.0	0.0	0	none	1.0	none	2.0	0.0	2016-08-26	65.0	6.0	23.9	187.0	4.0
248242	Budapest XI.	1111.0	brick flat (for sale)	4	3	-1.0	0.0	2	none	0.0	yes	1.0	1.0	2016-08-27	55.0	3.0	33.5	48.0	1.0
248243	Budapest VIII.	1081.0	brick flat (for sale)	2	3	4.0	0.0	2	none	0.0	yes	2.0	0.0	2016-08-28	55.0	8.0	18.0	115.0	3.0
248244	Budapest XIV.	1141.0	brick flat (for sale)	3	1	-1.0	0.0	0	none	1.0	none	1.0	0.0	2016-08-29	25.0	0.0	9.0	56.0	1.0

Most frequently occurring

	city	postcode	property_subtype	property_condition_type	property_floor	building_floor_count	view_type	orientation	garden_access	heating_type	elevator_type	room_cnt	small_room_cnt	created_at	property_area	balcony_area	price_created_at	ad_view_cnt	active_days	# duplicates
0	Budapest I.	1011.0	brick flat (for sale)	3	1	2.0	2.0	3	none	2.0	yes	1.0	1.0	2015-03-02	40.0	0.0	17.6	52.0	31.0	2
1	Budapest I.	1011.0	brick flat (for sale)	3	3	-1.0	0.0	2	none	1.0	yes	1.0	0.0	2016-01-27	35.0	0.0	23.9	17.0	13.0	2
2	Budapest I.	1015.0	brick flat (for sale)	3	3	-1.0	1.0	1	none	2.0	yes	2.0	0.0	2015-10-14	50.0	0.0	27.0	53.0	20.0	2
3	Budapest II.	1021.0	brick flat (for sale)	2	2	2.0	2.0	1	none	2.0	yes	1.0	1.0	2016-02-21	60.0	0.0	25.9	34.0	2.0	2
4	Budapest II.	1021.0	brick flat (for sale)	3	4	-1.0	0.0	3	none	2.0	yes	1.0	1.0	2016-07-08	40.0	0.0	26.9	14.0	17.0	2
5	Budapest III.	1031.0	brick flat (for sale)	3	2	-1.0	0.0	3	none	1.0	none	1.0	0.0	2016-06-22	35.0	0.0	16.2	21.0	16.0	2
6	Budapest III.	1031.0	prefabricated panel flat (for sale)	4	4	-1.0	0.0	3	none	2.0	yes	2.0	0.0	2016-05-09	50.0	0.0	21.2	21.0	29.0	2
7	Budapest III.	1034.0	brick flat (for sale)	4	3	-1.0	0.0	2	none	4.0	yes	1.0	0.0	2015-11-30	45.0	5.0	25.7	8.0	17.0	2
8	Budapest III.	1034.0	brick flat (for sale)	4	3	-1.0	0.0	2	none	4.0	yes	1.0	0.0	2016-04-08	40.0	5.0	25.9	32.0	49.0	2
9	Budapest III.	1039.0	prefabricated panel flat (for sale)	2	3	-1.0	0.0	0	none	2.0	yes	2.0	0.0	2016-05-24	50.0	4.0	14.7	40.0	28.0	2

Overview

Variables

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(unknown)

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Length

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(unknown)

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(unknown)

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Length

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(unknown)

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(unknown)

Most occurring blocks

Most frequent character per block

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Common Values

Length

Common Values (Plot)

Most occurring characters

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(unknown)

Most occurring scripts

Most frequent character per script

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(unknown)

Common Values

Length

Common Values (Plot)

Most occurring characters

Most occurring categories

Most frequent character per category

(unknown)

Most occurring scripts

Most frequent character per script

(unknown)

Most occurring blocks

Most frequent character per block

(unknown)

Common Values